Image Data Segmentation and Transmission

1. A method comprising: obtaining one or more source images as image data at an edge device; segmenting the one or more source images to generate a plurality of segments; determining a priority order for the plurality of segments based on a measurement of an effect of noise or quality degradation on objects in the one or more source images; and transmitting the plurality of segments to a remote computing device in the priority order, wherein the plurality of segments are generated as components, including spatial components generated by spatial decomposition of the one or more source images and/or frequency components that are generated by frequency decomposition of the one or more source images; and the priority order is determined by: adding the noise to or performing the quality degradation on the components, and obtaining the measurement of the effect of the noise or the quality degradation on the objects in the one or more source images.

2. The method of claim 1 , wherein the components comprise the frequency components; and the frequency decomposition is a degradation of image quality.

3. The method of claim 1 , wherein the components comprise the frequency components; and the frequency decomposition is a decomposition of a frequency of visual characteristics of the one or more source images.

4. The method of claim 1 , wherein the components comprise the frequency components; and the one or more source images are encoded in a compression format that supports the frequency decomposition.

5. The method of claim 4 , wherein the compression format is one of JPEG XR, JPEG 2000, and AV1.

6. The method of claim 1 , wherein the components comprise the spatial components; and the spatial components are generated via at least one of human input or a machine learning algorithm trained on labeled visual features.

7. The method of claim 1 , wherein the components comprise the spatial components and the frequency components; and when generating the plurality of segments, the frequency components are generated first, followed by the spatial components for each of the frequency components.

8. The method of claim 1 , further comprising: applying an application sensitivity algorithm to add the noise to or perform the quality degradation on each component.

9. The method of claim 1 , wherein the plurality of source images are filtered to select a subset of the plurality of source images to segment and transmit.

10. The method of claim 9 , wherein the subset of the plurality of source images are images of a target object for analysis.

11. A computing device, comprising: a logic subsystem comprising one or more processors; and memory storing instructions executable by the logic subsystem to: obtain one or more source images; segment the one or more source images to generate a plurality of segments; determine a priority order for the plurality of segments based on a measurement of an effect of noise or quality degradation on objects in the one or more source images; and transmit the plurality of segments to a remote computing device in the priority order, wherein the plurality of segments are components, including spatial components generated by spatial decomposition of the one or more source images and/or frequency components that are generated by frequency decomposition of the one or more source images; and the priority order is determined by: adding the noise to or performing the quality degradation on the components, and obtaining the measurement of the effect of the noise or the quality degradation on the objects in the one or more source images.

12. The computing device of claim 11 , wherein the components comprise the frequency components; and the frequency decomposition is a degradation of image quality.

13. The computing device of claim 11 , wherein the components comprise the frequency components; and the frequency decomposition is a decomposition of a frequency of visual characteristics of the one or more source images.

14. The computing device of claim 11 , wherein the components comprise the frequency components; and the one or more source images are encoded in a compression format that supports the frequency decomposition.

15. The computing device of claim 11 , wherein the components comprise the spatial components; and the spatial components are generated via at least one of human input or a machine learning algorithm trained on labeled visual features.

16. The computing device of claim 11 , wherein the components comprise the spatial components and the frequency components; and when generating the plurality of segments, the frequency components are generated first, followed by the spatial components for each of the frequency components.

17. The computing device of claim 11 , wherein applying an application sensitivity algorithm is applied to add the noise to or perform the quality degradation on each component.

18. The computing device of claim 11 , wherein the plurality of source images are filtered to select a subset of the plurality of source images to segment and transmit.

19. The computing device of claim 18 , wherein the subset of the plurality of source images are images of a target object for analysis.

20. A computing device, comprising: a logic subsystem comprising one or more processors; and memory storing instructions executable by the logic subsystem to: obtain one or more audio data; segment the one or more audio data to generate a plurality of segments; determine a priority order for the plurality of segments based on a measurement of an effect of noise or quality degradation in the one or more audio data; and transmit the plurality of segments to a remote computing device in the priority order, wherein the plurality of segments are frequency components that are generated by frequency decomposition of the one or more audio data; and the priority order is determined by: adding the noise to or performing the quality degradation on the frequency components, and obtaining the measurement of the effect of the noise or the quality degradation in the one or more audio data.